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For release 10:00 a.m. (EDT), Wednesday, July 7, 2010 USDL-10-0932 Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew Media Contact: (202) 691-5902 * PressOffice@bls.gov County Employment and Wages Fourth Quarter 2009 From December 2008 to December 2009, employment declined in 325 of the 334 largest U.S. counties according to preliminary data, the U.S. Bureau of Labor Statistics reported today. Trumbull, Ohio, posted the largest percentage decline, with a loss of 8.6 percent over the year, compared with a national job decrease of 4.1 percent. Almost 54 percent of the employment decline in Trumbull occurred in manufacturing, which lost 3,504 jobs over the year (-22.7 percent). Arlington, Va., experienced the largest over-the-year percentage increase in employment among the largest counties in the U.S., with a gain of 0.5 percent. The U.S. average weekly wage increased by 2.5 percent over the year. Among the large counties in the U.S., Douglas, Colo., had the largest over-the-year increase in average weekly wages in the fourth quarter of 2009, with a gain of 26.1 percent. Within Douglas, professional and business services had the largest over-the-year increase in average weekly wages with a gain of 99.8 percent. A fourth-quarter acquisition in this industry resulted in large payouts, which may include bonuses, severance pay, and stock options. St. Louis City, Mo., experienced the largest decline in average weekly wages with a loss of 33.9 percent over the year. This decline reflects a return from very high levels in 2008 caused by an acquisition in professional and business services and manufacturing. ---------------------------------------------------------------------- | | | A redesign of the County Employment and Wages news release will be | | implemented with the first quarter 2010 release. Table 3, along with | | the associated text on the largest county by state, will be removed. | | | ---------------------------------------------------------------------- Table A. Top 10 large counties ranked by December 2009 employment, December 2008-09 employment decrease, and December 2008-09 percent decrease in employment -------------------------------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------------------------------- December 2009 employment | Decrease in employment, | Percent decrease in employment, (thousands) | December 2008-09 | December 2008-09 | (thousands) | -------------------------------------------------------------------------------------------------------- | | United States 128,334.9| United States -5,521.5| United States -4.1 -------------------------------------------------------------------------------------------------------- | | Los Angeles, Calif. 3,926.0| Los Angeles, Calif. -217.9| Trumbull, Ohio -8.6 Cook, Ill. 2,369.9| Maricopa, Ariz. -113.0| Oakland, Mich. -8.1 New York, N.Y. 2,294.4| Cook, Ill. -111.1| Peoria, Ill. -8.0 Harris, Texas 1,990.2| New York, N.Y. -93.6| Seminole, Fla. -7.9 Maricopa, Ariz. 1,626.8| Harris, Texas -90.0| Sedgwick, Kan. -7.7 Dallas, Texas 1,409.9| Orange, Calif. -89.7| Tulare, Calif. -7.6 Orange, Calif. 1,361.4| San Diego, Calif. -64.6| Winnebago, Ill. -7.6 San Diego, Calif. 1,245.3| Dallas, Texas -63.6| Catawba, N.C. -7.5 King, Wash. 1,119.1| Clark, Nev. -60.7| Kern, Calif. -7.4 Miami-Dade, Fla. 959.7| Santa Clara, Calif. -56.8| Macomb, Mich. -7.3 | | -------------------------------------------------------------------------------------------------------- Of the 334 largest counties in the United States (as measured by 2008 annual average employment), 159 had over-the-year percentage declines in employment greater than or equal to the national average (-4.1 percent) in December 2009, 166 large counties experienced smaller declines than the national average, and 3 counties experienced employment gains. The percent change in average weekly wages was equal to or greater than the national average (2.5 percent) in 196 of the largest U.S. counties and was below the national average in 133 counties. The employment and average weekly wage data by county are compiled under the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from reports submitted by every employer subject to unemployment insurance (UI) laws. The 9.1 million employer reports cover 128.3 million full- and part-time workers. Large County Employment In December 2009, national employment, as measured by the QCEW program, was 128.3 million, down by 4.1 percent from December 2008. The 334 U.S. counties with 75,000 or more employees accounted for 71.4 percent of total U.S. employment and 77.1 percent of total wages. These 334 counties had a net job decline of 4,119,900 over the year, accounting for 74.6 percent of the overall U.S. employment decrease. Employment declined in 325 counties from December 2008 to December 2009. The largest percentage decline in employment was in Trumbull, Ohio (-8.6 percent). Oakland, Mich., had the next largest percentage decline (-8.1 percent), followed by the counties of Peoria, Ill. (-8.0 percent), Seminole, Fla. (-7.9 percent), and Sedgwick, Kan. (-7.7 percent). The largest decline in employment levels occurred in Los Angeles, Calif. (-217,900), followed by the counties of Maricopa, Ariz. (-113,000), Cook, Ill. (-111,100), New York, N.Y. (-93,600), and Harris, Texas (-90,000). (See table A.) Combined employment losses in these five counties over the year totaled 625,600, or 11.3 percent of the employment decline for the U.S. as a whole. Table B. Top 10 large counties ranked by fourth quarter 2009 average weekly wages, fourth quarter 2008-09 increase in average weekly wages, and fourth quarter 2008-09 percent increase in average weekly wages -------------------------------------------------------------------------------------------------------- Average weekly wage in large counties -------------------------------------------------------------------------------------------------------- Average weekly wage, | Increase in average weekly | Percent increase in average fourth quarter 2009 | wage, fourth quarter 2008-09 | weekly wage, fourth | | quarter 2008-09 -------------------------------------------------------------------------------------------------------- | | United States $942| United States $23| United States 2.5 -------------------------------------------------------------------------------------------------------- | | New York, N.Y. $1,878| Douglas, Colo. $244| Douglas, Colo. 26.1 Santa Clara, Calif. 1,699| Santa Clara, Calif. 129| Alachua, Fla. 10.1 Washington, D.C. 1,614| Durham, N.C. 108| Durham, N.C. 9.5 Fairfield, Conn. 1,607| Arlington, Va. 87| Elkhart, Ind. 8.6 Arlington, Va. 1,594| Montgomery, Md. 76| Santa Clara, Calif. 8.2 Suffolk, Mass. 1,565| Alachua, Fla. 74| Montgomery, Ala. 8.0 San Francisco, Calif. 1,539| Fairfax, Va. 73| McLean, Ill. 7.9 Fairfax, Va. 1,489| Montgomery, Ala. 66| Okaloosa, Fla. 7.5 San Mateo, Calif. 1,477| McLean, Ill. 66| McLennan, Texas 7.4 Morris, N.J. 1,429| Morris, N.J. 64| Lucas, Ohio 7.0 | Montgomery, Pa. 64| | | -------------------------------------------------------------------------------------------------------- Employment rose in three of the large counties from December 2008 to December 2009. Arlington, Va., had the largest over-the-year percentage increase in employment (0.5 percent), followed by Bronx, N.Y., and Kings, N.Y. (0.2 percent each). Large County Average Weekly Wages Average weekly wages for the nation increased by 2.5 percent over the year ending in the fourth quarter of 2009. Among the 334 largest counties, 305 had over-the-year increases in average weekly wages in the fourth quarter. The largest wage gain occurred in Douglas, Colo., with an increase of 26.1 percent from the fourth quarter of 2008. Alachua, Fla., had the second largest gain (10.1 percent), followed by the counties of Durham, N.C. (9.5 percent), Elkhart, Ind. (8.6 percent), and Santa Clara, Calif. (8.2 percent). (See table B.) Of the 334 largest counties, 23 experienced declines in average weekly wages. St. Louis City, Mo., led the nation in average weekly wage decline with a loss of 33.9 percent over the year. Within St. Louis City, large payouts related to an acquisition were distributed within professional and business services and manufacturing industries in the fourth quarter of 2008. Manufacturing had the largest over-the-year decline in average weekly wages (-57.9 percent) followed by professional and business services (-56.2 percent). Somerset, N.J., had the second largest overall decline (-6.2 percent), followed by the counties of Clayton, Ga. (-5.3 percent), Calcasieu, La. (-5.1 percent), and Lake, Ind. (-3.4 percent). The national average weekly wage in the fourth quarter of 2009 was $942. Average weekly wages were higher than the national average in 105 of the 334 largest U.S. counties. New York, N.Y., held the top position among the highest-paid large counties with an average weekly wage of $1,878. Santa Clara, Calif., was second with an average weekly wage of $1,699, followed by Washington, D.C. ($1,614), Fairfield, Conn. ($1,607), and Arlington, Va. ($1,594). There were 226 counties with an average weekly wage below the national average in the fourth quarter of 2009. The lowest average weekly wage was reported in Horry, S.C. ($584), followed by the counties of Cameron, Texas, Hidalgo, Texas ($598 each), Webb, Texas ($619), and Yakima, Wash. ($640). (See table 1.) Average weekly wages are affected not only by changes in total wages but also by employment changes in high- and low-paying industries. (See Technical Note.) The 2.5-percent over-the-year increase in average weekly wages for the nation was partially due to large employment declines in low-paying industries such as trade, transportation, and utilities. (See table 2.) Ten Largest U.S. Counties All of the 10 largest counties (based on 2008 annual average employment levels) experienced over-the-year percent declines in employment in December 2009. Maricopa, Ariz., experienced the largest decline in employment among the 10 largest counties with a 6.5 percent decrease. Within Maricopa, every private industry group except education and health services experienced an employment decline, with construction experiencing the largest decline (-28.5 percent). (See table 2.) Orange, Calif., had the next largest decline in employment (-6.2 percent), followed by Los Angeles, Calif. (-5.3 percent). New York, N.Y., experienced the smallest decline in employment (-3.9 percent) among the 10 largest counties. Dallas, Texas, and Harris, Texas, had the second smallest employment losses (-4.3 percent each). All of the 10 largest U.S. counties saw an over-the-year increase in average weekly wages. San Diego, Claif., experienced the largest increase in average weekly wages among the 10 largest counties with a gain of 3.7 percent. This average weekly wage growth was a result of a large employment loss in the professional and business services supersector. Employment dropped by 7.2 percent while total wages only dropped by 2.7 percent, thus average weekly wages for this supersector increased by 4.8 percent. San Diego’s average weekly wage growth was followed by King, Wash. (3.6 percent), and Maricopa, Ariz. (3.4 percent). Largest County by State Table 3 shows December 2009 employment and the 2009 fourth quarter average weekly wage in the largest county in each state, which is based on 2008 annual average employment levels. The employment levels in the counties ranged from 3.9 million in Los Angeles, Calif., to 42,600 in Laramie, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($1,878), while the lowest average weekly wage was in Yellowstone, Mont. ($768). For More Information The tables included in this release contain data for the nation and for the 334 U.S. counties with annual average employment levels of 75,000 or more in 2008. December 2009 employment and 2009 fourth quarter average weekly wages for all states are provided in table 4 of this release. For additional information about the quarterly employment and wages data, please read the Technical Note. Data for the fourth quarter of 2009 will be available at http://www.bls.gov/cew/. Additional information about the QCEW data may be obtained by calling (202) 691- 6567. Several BLS regional offices are issuing QCEW news releases targeted to local data users. For links to these releases, see http://www.bls.gov/cew/cewregional.htm. _____________ The County Employment and Wages release for first quarter 2010 is scheduled to be released on Tuesday, October 19, 2010. ---------------------------------------------------------------------- | | | The QCEW State and County Map application was released on June 30, | | 2010 (http://beta.bls.gov/maps). This new feature of the BLS | | website provides users with supersector industry employment and | | wages at the national, state, and county levels. Data are presented | | in map, tabular, and downloadable formats. | | | ----------------------------------------------------------------------
Technical Note These data are the product of a federal-state cooperative program, the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from summaries of employment and total pay of workers covered by state and federal unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The summaries are a result of the administration of state unemployment insurance programs that require most employers to pay quarterly taxes based on the employment and wages of workers covered by UI. QCEW data in this release are based on the 2007 North American Industry Classification System. Data for 2009 are preliminary and subject to revision. For purposes of this release, large counties are defined as having employment le- vels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are pro- vided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the basis of the prelimi- nary annual average of employment for the previous year. The 335 counties presented in this release were derived using 2008 preliminary annual averages of employment. For 2009 data, two counties have been added to the publication tables: Johnson, Iowa, and Gregg, Texas. These counties will be included in all 2009 quarterly re- leases. Two counties, Boone, Ky., and St. Tammany, La., which were published in the 2008 releases, will be excluded from this and future 2009 releases because their 2008 annual average employment levels were less than 75,000. The counties in table 2 are selected and sorted each year based on the annual average employment from the preceding year. The preliminary QCEW data presented in this release may differ from data released by the individual states. These potential differences result from the states' con- tinuing receipt of UI data over time and ongoing review and editing. The individual states determine their data release timetables. Differences between QCEW, BED, and CES employment measures The Bureau publishes three different establishment-based employment measures for any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)--makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, estimation procedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program dif- ferences and the intended uses of the program products. (See table.) Additional in- formation on each program can be obtained from the program Web sites shown in the table. Summary of Major Differences between QCEW, BED, and CES Employment Measures --------------------------------------------------------------------------------- | QCEW | BED | CES -----------|---------------------|----------------------|------------------------ Source |--Count of UI admini-|--Count of longitudi- |--Sample survey: | strative records | nally-linked UI ad- | 400,000 establish- | submitted by 9.1 | ministrative records| ments | million establish- | submitted by 6.8 | | ments in first | million private-sec-| | quarter of 2009 | tor employers | -----------|---------------------|----------------------|------------------------ Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal- | age, including all | ing government, pri-| ary jobs: | employers subject | vate households, and|--UI coverage, exclud- | to state and fed- | establishments with | ing agriculture, pri- | eral UI laws | zero employment | vate households, and | | | self-employed workers | | |--Other employment, in- | | | cluding railroads, | | | religious organiza- | | | tions, and other non- | | | UI-covered jobs -----------|---------------------|----------------------|------------------------ Publication|--Quarterly |--Quarterly |--Monthly frequency | -7 months after the| -8 months after the | -Usually first Friday | end of each quar- | end of each quarter| of following month | ter | | -----------|---------------------|----------------------|------------------------ Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam- file | and publishes each | quarter to longitu- | pling frame and annu- | new quarter of UI | dinal database and | ally realigns (bench- | data | directly summarizes | marks) sample esti- | | gross job gains and | mates to first quar- | | losses | ter UI levels -----------|---------------------|----------------------|------------------------ Principal |--Provides a quarter-|--Provides quarterly |--Provides current month- products | ly and annual uni- | employer dynamics | ly estimates of employ- | verse count of es- | data on establish- | ment, hours, and earn- | tablishments, em- | ment openings, clos-| ings at the MSA, state, | ployment, and wages| ings, expansions, | and national level by | at the county, MSA,| and contractions at | industry | state, and national| the national level | | levels by detailed | by NAICS supersec- | | industry | tors and by size of | | | firm, and at the | | | state private-sector| | | total level | | |--Future expansions | | | will include data | | | with greater indus- | | | try detail and data | | | at the county and | | | MSA level | -----------|---------------------|----------------------|------------------------ Principal |--Major uses include:|--Major uses include: |--Major uses include: uses | -Detailed locality | -Business cycle | -Principal national | data | analysis | economic indicator | -Periodic universe | -Analysis of employ-| -Official time series | counts for bench- | er dynamics under- | for employment change | marking sample | lying economic ex- | measures | survey estimates | pansions and con- | -Input into other ma- | -Sample frame for | tractions | jor economic indi- | BLS establishment | -Analysis of employ-| cators | surveys | ment expansion and | | | contraction by size| | | of firm | | | | -----------|---------------------|----------------------|------------------------ Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/ Web sites | | | --------------------------------------------------------------------------------- Coverage Employment and wage data for workers covered by state UI laws are compiled from quarterly contribution reports submitted to the SWAs by employers. For federal ci- vilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program, employment and wage data are compiled from quarterly reports sub- mitted by four major federal payroll processing centers on behalf of all federal agencies, with the exception of a few agencies which still report directly to the individual SWA. In addition to the quarterly contribution reports, employers who operate multiple establishments within a state complete a questionnaire, called the "Multiple Worksite Report," which provides detailed information on the location and industry of each of their establishments. QCEW employment and wage data are derived from microdata summaries of 9.1 million employer reports of employment and wages submitted by states to the BLS in 2008. These reports are based on place of employ- ment rather than place of residence. UI and UCFE coverage is broad and has been basically comparable from state to state since 1978, when the 1976 amendments to the Federal Unemployment Tax Act became ef- fective, expanding coverage to include most State and local government employees. In 2008, UI and UCFE programs covered workers in 134.8 million jobs. The estimated 129.4 million workers in these jobs (after adjustment for multiple jobholders) represented 95.5 percent of civilian wage and salary employment. Covered workers received $6.142 trillion in pay, representing 93.8 percent of the wage and salary component of personal income and 42.5 percent of the gross domestic product. Major exclusions from UI coverage include self-employed workers, most agricultural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domestic workers, most student workers at schools, and employees of certain small nonprofit organizations. State and federal UI laws change periodically. These changes may have an impact on the employment and wages reported by employers covered under the UI program. Cover- age changes may affect the over-the-year comparisons presented in this news re- lease. Concepts and methodology Monthly employment is based on the number of workers who worked during or received pay for the pay period including the 12th of the month. With few exceptions, all employees of covered firms are reported, including production and sales workers, corporation officials, executives, supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also are included. Average weekly wage values are calculated by dividing quarterly total wages by the average of the three monthly employment levels (all employees, as described above) and dividing the result by 13, for the 13 weeks in the quarter. These calculations are made using unrounded employment and wage values. The average wage values that can be calculated using rounded data from the BLS database may differ from the av- erages reported. Included in the quarterly wage data are non-wage cash payments such as bonuses, the cash value of meals and lodging when supplied, tips and other gratuities, and, in some states, employer contributions to certain deferred compen- sation plans such as 401(k) plans and stock options. Over-the-year comparisons of average weekly wages may reflect fluctuations in average monthly employment and/or total quarterly wages between the current quarter and prior year levels. Average weekly wages are affected by the ratio of full-time to part-time workers as well as the number of individuals in high-paying and low-paying occupations and the incidence of pay periods within a quarter. For instance, the average weekly wage of the work force could increase significantly when there is a large decline in the number of employees that had been receiving below-average wages. Wages may include payments to workers not present in the employment counts because they did not work during the pay period including the 12th of the month. When comparing average week- ly wage levels between industries, states, or quarters, these factors should be taken into consideration. Federal government pay levels are subject to periodic, sometimes large, fluctua- tions due to a calendar effect that consists of some quarters having more pay pe- riods than others. Most federal employees are paid on a biweekly pay schedule. As a result of this schedule, in some quarters, federal wages contain payments for six pay periods, while in other quarters their wages include payments for seven pay pe- riods. Over-the-year comparisons of average weekly wages may reflect this calendar effect. Higher growth in average weekly wages may be attributed, in part, to a com- parison of quarterly wages for the current year, which include seven pay periods, with year-ago wages that reflect only six pay periods. An opposite effect will oc- cur when wages in the current period, which contain six pay periods, are compared with year-ago wages that include seven pay periods. The effect on over-the-year pay comparisons can be pronounced in federal government due to the uniform nature of federal payroll processing. This pattern may exist in private sector pay; however, because there are more pay period types (weekly, biweekly, semimonthly, monthly) it is less pronounced. The effect is most visible in counties with large concentra- tions of federal employment. In order to ensure the highest possible quality of data, states verify with employ- ers and update, if necessary, the industry, location, and ownership classification of all establishments on a 4-year cycle. Changes in establishment classification codes resulting from this process are introduced with the data reported for the first quarter of the year. Changes resulting from improved employer reporting also are introduced in the first quarter. QCEW data are not designed as a time series. QCEW data are simply the sums of indi- vidual establishment records and reflect the number of establishments that exist in a county or industry at a point in time. Establishments can move in or out of a county or industry for a number of reasons--some reflecting economic events, others reflecting administrative changes. For example, economic change would come from a firm relocating into the county; administrative change would come from a company correcting its county designation. The over-the-year changes of employment and wages presented in this release have been adjusted to account for most of the administrative corrections made to the un- derlying establishment reports. This is done by modifying the prior-year levels used to calculate the over-the-year changes. Percent changes are calculated using an adjusted version of the final 2008 quarterly data as the base data. The adjusted prior-year levels used to calculate the over-the-year percent change in employment and wages are not published. These adjusted prior-year levels do not match the un- adjusted data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news re- lease. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes--those occurring when employers update the industry, location, and ownership information of their estab- lishments. The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. In- cluded in these adjustments are administrative changes involving the classification of establishments that were previously reported in the unknown or statewide county or unknown industry categories. Beginning with the first quarter of 2008, adjusted data account for administrative changes caused by multi-unit employers who start reporting for each individual establishment rather than as a single entity. The adjusted data used to calculate the over-the-year change measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points (a 12-month period) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Stan- dards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more common designation used in New England (and New Jersey). The regions referred to in this release are defined as census regions. Additional statistics and other information An annual bulletin, Employment and Wages, features comprehensive information by de- tailed industry on establishments, employment, and wages for the nation and all states. The 2008 edition of this bulletin contains selected data produced by Busi- ness Employment Dynamics (BED) on job gains and losses, as well as selected data from the first quarter 2009 version of this news release. Tables and additional content from the 2008 Employment and Wages Annual Bulletin are now available online at http://www.bls.gov/cew/cewbultn08.htm. These tables present final 2008 annual averages. The tables are included on the CD which accompanies the hardcopy version of the Annual Bulletin. Employment and Wages Annual Averages, 2008 is available for sale as a chartbook from the United States Government Printing Office, Superin- tendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone (866) 512- 1800, outside Washington, D.C. Within Washington, D.C., the telephone number is (202) 512-1800. The fax number is (202) 512-2104. News releases on quarterly measures of gross job flows also are available upon re- quest from the Division of Administrative Statistics and Labor Turnover (Business Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail: BDMInfo@bls.gov). Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; TDD message referral phone number: 1- 800-877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 335 largest counties, fourth quarter 2009(2) Employment Average weekly wage(4) Establishments, County(3) fourth quarter Percent Ranking Percent Ranking 2009 December change, by Average change, by (thousands) 2009 December percent weekly fourth percent (thousands) 2008-09(5) change wage quarter change 2008-09(5) United States(6)......... 9,085.0 128,334.9 -4.1 - $942 2.5 - Jefferson, AL............ 18.1 336.1 -5.6 263 946 2.5 193 Madison, AL.............. 8.8 179.8 -1.6 20 1,047 4.9 41 Mobile, AL............... 9.8 165.8 -5.1 241 828 2.5 193 Montgomery, AL........... 6.4 130.0 -3.7 140 891 8.0 6 Shelby, AL............... 4.8 70.7 -6.5 302 849 1.6 247 Tuscaloosa, AL........... 4.4 82.2 -4.6 209 798 1.9 230 Anchorage Borough, AK.... 8.2 147.6 -0.3 6 1,005 3.5 114 Maricopa, AZ............. 98.7 1,626.8 -6.5 302 923 3.4 119 Pima, AZ................. 20.2 350.9 -4.8 221 829 3.4 119 Benton, AR............... 5.5 90.9 -3.6 134 854 0.9 280 Pulaski, AR.............. 15.1 244.2 -2.7 64 863 1.6 247 Washington, AR........... 5.6 89.0 -2.4 50 774 3.9 87 Alameda, CA.............. 54.3 628.3 -6.6 305 1,195 2.8 167 Butte, CA................ 8.0 71.4 -3.7 140 720 3.4 119 Contra Costa, CA......... 30.0 318.4 -5.6 263 1,132 0.3 301 Fresno, CA............... 30.9 323.7 -6.5 302 759 2.8 167 Kern, CA................. 18.3 260.4 -7.4 320 820 2.0 227 Los Angeles, CA.......... 434.0 3,926.0 -5.3 248 1,099 2.0 227 Marin, CA................ 11.8 102.4 -5.6 263 1,163 1.0 276 Monterey, CA............. 12.9 141.4 -7.0 312 821 2.4 197 Orange, CA............... 102.8 1,361.4 -6.2 295 1,065 2.0 227 Placer, CA............... 10.9 122.0 -7.0 312 920 3.0 141 Riverside, CA............ 48.4 559.7 -6.4 300 757 1.7 244 Sacramento, CA........... 54.5 587.0 -4.1 170 1,019 1.3 262 San Bernardino, CA....... 50.6 606.0 -5.8 276 806 2.3 208 San Diego, CA............ 99.4 1,245.3 -4.9 225 1,019 3.7 103 San Francisco, CA........ 52.9 548.0 -4.5 201 1,539 3.1 136 San Joaquin, CA.......... 17.8 202.3 -6.0 287 816 2.4 197 San Luis Obispo, CA...... 9.7 95.7 -6.1 289 798 4.2 74 San Mateo, CA............ 24.1 324.1 -5.2 245 1,477 2.6 180 Santa Barbara, CA........ 14.5 169.5 -6.2 295 895 3.2 129 Santa Clara, CA.......... 61.6 846.5 -6.3 297 1,699 8.2 5 Santa Cruz, CA........... 9.2 86.4 -4.0 162 819 -0.2 308 Solano, CA............... 10.2 120.5 -3.8 147 921 1.9 230 Sonoma, CA............... 18.9 174.2 -6.3 297 886 -1.1 313 Stanislaus, CA........... 15.2 155.5 -6.8 310 790 4.4 61 Tulare, CA............... 9.6 140.9 -7.6 322 666 4.4 61 Ventura, CA.............. 24.0 295.5 -5.7 272 959 2.6 180 Yolo, CA................. 6.0 93.7 -6.0 287 882 -0.1 307 Adams, CO................ 9.0 147.7 -5.3 248 849 1.4 257 Arapahoe, CO............. 18.8 269.9 -3.8 147 1,094 3.8 96 Boulder, CO.............. 12.8 152.8 -3.8 147 1,069 3.2 129 Denver, CO............... 25.0 420.2 -4.7 215 1,154 3.4 119 Douglas, CO.............. 9.3 89.9 -4.8 221 1,179 26.1 1 El Paso, CO.............. 16.8 232.7 -3.7 140 863 3.6 110 Jefferson, CO............ 18.0 202.9 -4.0 162 969 4.4 61 Larimer, CO.............. 10.1 124.6 -4.2 178 841 0.5 293 Weld, CO................. 5.8 77.1 -6.6 305 772 1.3 262 Fairfield, CT............ 32.9 401.6 -4.5 201 1,607 0.7 288 Hartford, CT............. 25.4 486.0 -3.8 147 1,153 3.6 110 New Haven, CT............ 22.4 353.3 -3.6 134 1,013 3.7 103 New London, CT........... 7.0 125.7 -3.8 147 942 3.5 114 New Castle, DE........... 17.8 264.6 -5.9 282 1,070 1.9 230 Washington, DC........... 34.8 686.7 -0.1 4 1,614 2.7 173 Alachua, FL.............. 6.7 116.7 -4.1 170 810 10.1 2 Brevard, FL.............. 14.7 189.1 -4.0 162 897 4.3 67 Broward, FL.............. 63.3 689.2 -5.6 263 900 2.4 197 Collier, FL.............. 11.9 117.5 -6.6 305 832 2.7 173 Duval, FL................ 26.9 436.8 -4.5 201 911 3.9 87 Escambia, FL............. 7.9 118.9 -3.3 107 760 5.6 22 Hillsborough, FL......... 37.2 574.9 -6.1 289 927 5.8 17 Lake, FL................. 7.3 80.4 -5.3 248 674 2.6 180 Lee, FL.................. 18.8 194.9 -5.6 263 781 2.9 153 Leon, FL................. 8.2 139.1 -2.4 50 815 4.2 74 Manatee, FL.............. 9.2 111.8 -4.0 162 708 2.2 214 Marion, FL............... 8.2 90.6 (7) - 677 (7) - Miami-Dade, FL........... 85.0 959.7 -4.5 201 949 2.9 153 Okaloosa, FL............. 6.0 75.6 -2.2 41 791 7.5 8 Orange, FL............... 35.4 648.2 -4.8 221 850 2.4 197 Palm Beach, FL........... 49.5 500.2 -5.4 253 967 5.2 33 Pasco, FL................ 9.8 96.6 -4.4 196 680 1.8 241 Pinellas, FL............. 31.0 389.2 -5.5 257 852 5.7 21 Polk, FL................. 12.5 192.8 -4.4 196 734 4.0 83 Sarasota, FL............. 14.8 134.6 -5.9 282 804 2.6 180 Seminole, FL............. 14.2 156.2 -7.9 325 791 0.8 285 Volusia, FL.............. 13.6 151.0 -4.9 225 680 2.7 173 Bibb, GA................. 4.6 79.4 -5.8 276 752 5.0 39 Chatham, GA.............. 7.7 127.9 -5.0 231 807 1.6 247 Clayton, GA.............. 4.4 107.3 -3.9 156 810 -5.3 327 Cobb, GA................. 20.7 296.4 -5.7 272 974 0.9 280 De Kalb, GA.............. 17.6 278.8 -4.2 178 971 4.7 46 Fulton, GA............... 39.3 697.4 -5.0 231 1,207 1.9 230 Gwinnett, GA............. 23.6 294.5 -5.7 272 907 1.3 262 Muscogee, GA............. 4.7 91.5 -3.9 156 757 5.1 35 Richmond, GA............. 4.8 99.3 -2.4 50 793 3.4 119 Honolulu, HI............. 25.0 435.3 -3.2 100 875 2.9 153 Ada, ID.................. 14.5 193.7 -4.9 225 824 1.5 252 Champaign, IL............ 4.2 89.3 -2.9 76 794 2.1 222 Cook, IL................. 142.6 2,369.9 -4.5 201 1,142 2.1 222 Du Page, IL.............. 36.4 548.0 -5.9 282 1,082 2.2 214 Kane, IL................. 12.9 190.3 -7.2 318 848 1.8 241 Lake, IL................. 21.4 311.4 -5.1 241 1,197 4.9 41 McHenry, IL.............. 8.6 93.5 -7.0 312 789 0.9 280 McLean, IL............... 3.7 83.7 -3.1 88 901 7.9 7 Madison, IL.............. 6.0 91.3 -4.5 201 801 4.2 74 Peoria, IL............... 4.7 97.9 -8.0 326 895 2.8 167 Rock Island, IL.......... 3.5 74.4 -6.1 289 1,115 2.9 153 St. Clair, IL............ 5.5 93.9 -3.1 88 782 3.7 103 Sangamon, IL............. 5.3 126.3 -2.3 47 928 3.5 114 Will, IL................. 14.2 188.4 -4.3 184 837 1.2 268 Winnebago, IL............ 6.9 123.8 -7.6 322 797 2.7 173 Allen, IN................ 9.1 170.7 -4.7 215 774 3.3 126 Elkhart, IN.............. 4.9 96.4 -4.8 221 744 8.6 4 Hamilton, IN............. 7.9 107.1 -5.1 241 873 2.2 214 Lake, IN................. 10.3 183.6 -5.3 248 798 -3.4 325 Marion, IN............... 24.0 547.0 -3.8 147 942 3.1 136 St. Joseph, IN........... 6.1 114.9 -5.5 257 799 5.1 35 Tippecanoe, IN........... 3.3 72.1 -6.8 310 800 3.8 96 Vanderburgh, IN.......... 4.8 104.7 -3.2 100 791 3.3 126 Johnson, IA.............. 3.5 74.5 -2.1 36 807 2.7 173 Linn, IA................. 6.3 123.6 -3.0 85 885 -1.1 313 Polk, IA................. 14.8 265.7 -3.1 88 933 3.1 136 Scott, IA................ 5.3 84.9 -4.6 209 763 1.6 247 Johnson, KS.............. 20.9 298.8 -5.0 231 982 3.4 119 Sedgwick, KS............. 12.5 241.3 -7.7 324 872 3.3 126 Shawnee, KS.............. 4.9 92.9 -2.9 76 798 5.4 30 Wyandotte, KS............ 3.2 79.0 -1.5 17 890 4.3 67 Fayette, KY.............. 9.4 172.9 -2.9 76 846 1.7 244 Jefferson, KY............ 22.0 409.9 -3.2 100 908 4.2 74 Caddo, LA................ 7.5 121.9 -2.7 64 790 1.4 257 Calcasieu, LA............ 5.0 83.1 -5.4 253 783 -5.1 326 East Baton Rouge, LA..... 14.7 259.1 -3.1 88 897 2.6 180 Jefferson, LA............ 14.2 194.5 -3.0 85 896 2.6 180 Lafayette, LA............ 9.1 129.6 -5.5 257 887 -2.6 324 Orleans, LA.............. 10.9 169.4 -1.5 17 1,007 0.5 293 Cumberland, ME........... 12.3 168.0 -3.2 100 863 4.7 46 Anne Arundel, MD......... 14.3 226.4 -3.1 88 1,019 5.6 22 Baltimore, MD............ 21.2 364.8 -3.4 117 1,004 4.0 83 Frederick, MD............ 5.9 91.4 -2.9 76 933 4.7 46 Harford, MD.............. 5.6 81.6 -1.1 11 896 6.2 12 Howard, MD............... 8.7 143.0 -2.9 76 1,131 4.0 83 Montgomery, MD........... 32.5 447.4 -2.1 36 1,294 6.2 12 Prince Georges, MD....... 15.5 304.2 -3.4 117 1,032 3.8 96 Baltimore City, MD....... 13.7 326.1 -3.4 117 1,113 1.2 268 Barnstable, MA........... 9.0 82.7 -1.9 27 834 2.7 173 Bristol, MA.............. 15.6 207.4 -4.1 170 866 2.2 214 Essex, MA................ 21.0 293.0 -2.0 32 1,013 3.6 110 Hampden, MA.............. 14.8 192.3 -3.6 134 893 2.8 167 Middlesex, MA............ 47.9 803.0 -2.8 70 1,344 3.5 114 Norfolk, MA.............. 23.6 312.9 -3.4 117 1,151 0.5 293 Plymouth, MA............. 13.6 171.3 -2.5 56 902 1.0 276 Suffolk, MA.............. 22.2 574.8 -3.5 128 1,565 -0.3 309 Worcester, MA............ 20.8 309.8 -3.0 85 947 1.6 247 Genesee, MI.............. 7.6 127.0 -5.5 257 826 3.0 141 Ingham, MI............... 6.6 151.1 -4.3 184 913 3.0 141 Kalamazoo, MI............ 5.5 108.0 -4.6 209 842 -1.3 317 Kent, MI................. 14.0 305.9 -5.0 231 855 2.4 197 Macomb, MI............... 17.2 270.8 -7.3 319 976 1.0 276 Oakland, MI.............. 37.9 607.1 -8.1 327 1,093 -0.5 311 Ottawa, MI............... 5.6 98.0 -5.9 282 787 -0.4 310 Saginaw, MI.............. 4.2 79.1 (7) - 782 (7) - Washtenaw, MI............ 8.0 184.2 -1.8 24 981 1.0 276 Wayne, MI................ 31.1 662.6 -7.1 317 1,036 0.5 293 Anoka, MN................ 7.4 105.8 -6.6 305 858 2.3 208 Dakota, MN............... 10.0 168.8 -2.6 62 920 2.6 180 Hennepin, MN............. 40.7 802.6 -4.3 184 1,152 0.7 288 Olmsted, MN.............. 3.4 87.3 -2.8 70 994 1.9 230 Ramsey, MN............... 14.5 316.0 -4.3 184 1,040 6.0 15 St. Louis, MN............ 5.7 92.2 -4.2 178 755 -0.7 312 Stearns, MN.............. 4.3 78.1 -3.3 107 747 5.8 17 Harrison, MS............. 4.6 83.4 -2.1 36 718 2.3 208 Hinds, MS................ 6.3 125.0 -2.4 50 832 3.4 119 Boone, MO................ 4.5 81.2 -1.7 22 719 4.2 74 Clay, MO................. 5.0 84.8 -5.2 245 856 4.3 67 Greene, MO............... 8.0 149.2 -4.2 178 711 3.9 87 Jackson, MO.............. 18.5 351.2 -4.3 184 958 3.2 129 St. Charles, MO.......... 8.2 117.8 -4.1 170 739 0.8 285 St. Louis, MO............ 32.1 571.0 -4.7 215 1,006 1.5 252 St. Louis City, MO....... 8.6 215.2 (7) - 996 -33.9 329 Yellowstone, MT.......... 5.9 75.7 -3.4 117 768 3.9 87 Douglas, NE.............. 15.9 312.1 -3.1 88 874 3.9 87 Lancaster, NE............ 8.2 153.2 -3.9 156 750 3.2 129 Clark, NV................ 49.4 809.7 -7.0 312 872 1.9 230 Washoe, NV............... 14.3 187.4 -7.0 312 868 0.1 304 Hillsborough, NH......... 12.1 188.3 -3.9 156 1,065 0.2 303 Rockingham, NH........... 10.8 131.9 -3.2 100 930 2.6 180 Atlantic, NJ............. 7.0 133.3 -4.5 201 832 1.2 268 Bergen, NJ............... 34.5 432.8 -3.8 147 1,205 1.7 244 Burlington, NJ........... 11.4 194.6 -2.7 64 1,011 3.8 96 Camden, NJ............... 13.0 198.8 -2.9 76 1,010 0.9 280 Essex, NJ................ 21.5 348.2 -2.7 64 1,211 2.7 173 Gloucester, NJ........... 6.4 100.4 -4.3 184 865 1.3 262 Hudson, NJ............... 14.1 232.4 -2.8 70 1,241 2.4 197 Mercer, NJ............... 11.2 226.1 -2.2 41 1,224 -2.2 322 Middlesex, NJ............ 22.1 385.0 -3.4 117 1,160 1.4 257 Monmouth, NJ............. 20.8 246.3 -3.3 107 1,032 1.3 262 Morris, NJ............... 18.1 274.3 -3.5 128 1,429 4.7 46 Ocean, NJ................ 12.4 144.3 -1.3 13 816 2.6 180 Passaic, NJ.............. 12.5 171.3 -3.1 88 997 2.3 208 Somerset, NJ............. 10.3 168.8 -3.3 107 1,413 -6.2 328 Union, NJ................ 14.9 221.3 -3.3 107 1,226 (7) - Bernalillo, NM........... 17.5 317.3 -3.7 140 850 4.4 61 Albany, NY............... 9.9 223.3 -2.6 62 963 1.9 230 Bronx, NY................ 16.4 232.7 0.2 2 919 3.5 114 Broome, NY............... 4.5 92.7 -3.3 107 753 3.7 103 Dutchess, NY............. 8.2 113.1 -2.8 70 942 4.7 46 Erie, NY................. 23.5 453.4 -2.5 56 817 3.0 141 Kings, NY................ 48.3 488.8 0.2 2 830 1.2 268 Monroe, NY............... 17.9 371.8 -2.9 76 887 3.0 141 Nassau, NY............... 52.4 595.3 -2.2 41 1,101 4.3 67 New York, NY............. 118.1 2,294.4 -3.9 156 1,878 1.1 273 Oneida, NY............... 5.3 109.3 -2.3 47 745 3.2 129 Onondaga, NY............. 12.7 246.1 -3.1 88 881 3.8 96 Orange, NY............... 9.9 131.4 -1.3 13 799 2.8 167 Queens, NY............... 44.2 499.4 -2.1 36 935 1.3 262 Richmond, NY............. 8.8 94.6 -1.1 11 850 2.9 153 Rockland, NY............. 9.8 114.3 -2.8 70 982 -2.1 321 Saratoga, NY............. 5.4 74.6 -2.5 56 792 3.9 87 Suffolk, NY.............. 50.0 608.5 -3.1 88 1,044 0.3 301 Westchester, NY.......... 36.0 406.5 -4.0 162 1,288 4.4 61 Buncombe, NC............. 7.8 110.7 -4.0 162 747 2.9 153 Catawba, NC.............. 4.4 77.3 -7.5 321 725 4.2 74 Cumberland, NC........... 6.2 119.6 -1.4 15 749 5.5 27 Durham, NC............... 7.1 177.3 -4.3 184 1,239 9.5 3 Forsyth, NC.............. 9.0 176.2 -4.6 209 849 2.9 153 Guilford, NC............. 14.3 260.1 -5.4 253 823 3.0 141 Mecklenburg, NC.......... 32.3 534.2 -5.7 272 1,042 2.5 193 New Hanover, NC.......... 7.3 95.3 -5.8 276 798 5.6 22 Wake, NC................. 28.5 430.7 -4.1 170 929 1.5 252 Cass, ND................. 5.9 99.3 -1.4 15 795 2.1 222 Butler, OH............... 7.3 138.2 -5.0 231 819 4.6 55 Cuyahoga, OH............. 36.7 689.8 -4.7 215 939 1.2 268 Franklin, OH............. 29.4 651.3 -3.7 140 918 4.3 67 Hamilton, OH............. 23.5 488.6 -4.6 209 1,007 2.4 197 Lake, OH................. 6.6 92.1 -6.7 309 777 2.8 167 Lorain, OH............... 6.2 91.8 -4.1 170 742 0.0 306 Lucas, OH................ 10.5 198.5 -5.5 257 830 7.0 10 Mahoning, OH............. 6.2 97.7 -2.7 64 683 1.9 230 Montgomery, OH........... 12.5 242.1 -5.5 257 846 2.9 153 Stark, OH................ 8.9 149.2 -5.8 276 713 1.4 257 Summit, OH............... 14.7 254.2 -6.3 297 842 2.1 222 Trumbull, OH............. 4.6 68.9 -8.6 328 739 -1.3 317 Warren, OH............... 4.2 71.7 -3.5 128 802 5.4 30 Oklahoma, OK............. 24.1 408.0 -4.4 196 870 1.9 230 Tulsa, OK................ 19.8 331.0 -5.6 263 845 0.8 285 Clackamas, OR............ 12.6 138.5 -5.3 248 842 2.4 197 Jackson, OR.............. 6.5 76.2 -5.8 276 688 3.1 136 Lane, OR................. 10.9 135.4 -5.9 282 729 2.5 193 Marion, OR............... 9.3 130.4 -3.4 117 727 2.3 208 Multnomah, OR............ 28.1 421.9 -4.9 225 953 1.9 230 Washington, OR........... 16.0 230.9 -5.0 231 1,031 4.5 58 Allegheny, PA............ 35.1 668.8 -2.4 50 1,003 2.9 153 Berks, PA................ 9.0 161.5 -3.8 147 849 3.8 96 Bucks, PA................ 19.7 249.3 -4.2 178 930 2.9 153 Butler, PA............... 4.8 79.5 -1.6 20 831 3.0 141 Chester, PA.............. 15.0 236.1 -3.3 107 1,233 5.4 30 Cumberland, PA........... 6.0 120.8 -3.4 117 869 6.0 15 Dauphin, PA.............. 7.4 177.8 -2.1 36 924 4.3 67 Delaware, PA............. 13.5 205.2 -3.2 100 994 4.3 67 Erie, PA................. 7.6 120.9 -4.3 184 735 0.7 288 Lackawanna, PA........... 5.9 98.7 -2.9 76 736 3.1 136 Lancaster, PA............ 12.5 217.7 -4.2 178 789 2.2 214 Lehigh, PA............... 8.7 170.4 -3.7 140 921 1.5 252 Luzerne, PA.............. 7.8 137.5 -3.4 117 735 5.6 22 Montgomery, PA........... 27.4 469.0 -3.5 128 1,219 5.5 27 Northampton, PA.......... 6.5 97.7 -1.5 17 823 2.1 222 Philadelphia, PA......... 31.4 624.5 -2.4 50 1,145 4.7 46 Washington, PA........... 5.4 77.5 -3.7 140 847 4.2 74 Westmoreland, PA......... 9.4 130.2 -3.9 156 751 3.0 141 York, PA................. 9.0 168.8 -4.7 215 810 2.9 153 Kent, RI................. 5.5 73.7 -5.1 241 828 5.6 22 Providence, RI........... 17.7 267.0 -4.0 162 951 1.9 230 Charleston, SC........... 11.6 198.1 -5.6 263 821 5.1 35 Greenville, SC........... 12.4 224.0 -4.5 201 820 2.9 153 Horry, SC................ 7.9 100.1 -5.6 263 584 1.4 257 Lexington, SC............ 5.6 93.0 -5.0 231 710 4.1 82 Richland, SC............. 9.2 205.1 -4.3 184 826 4.7 46 Spartanburg, SC.......... 6.0 111.9 -5.4 253 803 3.7 103 Minnehaha, SD............ 6.5 113.2 -2.5 56 777 5.0 39 Davidson, TN............. 18.3 418.3 -4.0 162 996 2.2 214 Hamilton, TN............. 8.5 177.4 -6.1 289 821 0.6 292 Knox, TN................. 10.9 217.2 -4.4 196 835 4.5 58 Rutherford, TN........... 4.3 93.5 -4.6 209 846 0.4 299 Shelby, TN............... 19.4 471.5 -5.0 231 971 3.9 87 Williamson, TN........... 6.0 85.7 -2.9 76 1,012 3.0 141 Bell, TX................. 4.6 103.5 -0.7 7 741 5.1 35 Bexar, TX................ 33.0 719.1 -1.9 27 843 4.7 46 Brazoria, TX............. 4.7 84.0 -5.0 231 845 -2.3 323 Brazos, TX............... 3.9 87.2 (7) - 695 (7) - Cameron, TX.............. 6.4 123.7 -0.8 8 598 2.2 214 Collin, TX............... 17.5 282.4 (7) - 1,108 5.5 27 Dallas, TX............... 67.8 1,409.9 -4.3 184 1,129 0.5 293 Denton, TX............... 10.7 167.9 -1.8 24 827 2.2 214 El Paso, TX.............. 13.5 269.5 -1.7 22 684 6.4 11 Fort Bend, TX............ 8.8 128.9 -3.4 117 954 -2.0 320 Galveston, TX............ 5.2 93.1 -0.2 5 877 5.8 17 Gregg, TX................ 4.1 71.5 -5.6 263 821 -1.2 316 Harris, TX............... 98.7 1,990.2 -4.3 184 1,195 0.7 288 Hidalgo, TX.............. 10.7 220.4 -1.0 10 598 4.2 74 Jefferson, TX............ 5.9 119.8 -6.1 289 924 -1.5 319 Lubbock, TX.............. 6.9 123.9 -2.2 41 718 2.6 180 McLennan, TX............. 4.9 101.4 -2.0 32 772 7.4 9 Montgomery, TX........... 8.4 127.1 -2.0 32 879 0.5 293 Nueces, TX............... 8.0 151.2 (7) - 794 (7) - Potter, TX............... 3.9 74.9 -2.0 32 798 2.3 208 Smith, TX................ 5.3 92.2 -3.6 134 811 0.4 299 Tarrant, TX.............. 37.3 748.1 -3.1 88 947 3.2 129 Travis, TX............... 29.5 558.5 -3.3 107 1,036 2.6 180 Webb, TX................. 4.7 86.0 -3.5 128 619 3.0 141 Williamson, TX........... 7.4 120.2 -1.9 27 906 1.1 273 Davis, UT................ 7.2 99.2 -2.8 70 764 3.0 141 Salt Lake, UT............ 37.5 562.1 -4.1 170 888 4.7 46 Utah, UT................. 13.0 164.6 -4.4 196 741 1.8 241 Weber, UT................ 5.7 88.5 -5.0 231 705 3.7 103 Chittenden, VT........... 6.0 93.2 -2.3 47 937 4.6 55 Arlington, VA............ 8.0 160.9 0.5 1 1,594 5.8 17 Chesterfield, VA......... 7.6 115.0 -4.3 184 852 3.0 141 Fairfax, VA.............. 34.3 574.6 -1.9 27 1,489 5.2 33 Henrico, VA.............. 9.7 169.8 -5.8 276 945 2.9 153 Loudoun, VA.............. 9.2 131.1 -1.9 27 1,141 4.8 43 Prince William, VA....... 7.4 103.5 -0.8 8 848 3.9 87 Alexandria City, VA...... 6.1 98.6 -2.7 64 1,376 4.8 43 Chesapeake City, VA...... 5.7 94.9 -3.8 147 761 6.1 14 Newport News City, VA.... 3.9 96.4 -3.5 128 873 2.6 180 Norfolk City, VA......... 5.8 138.1 -3.1 88 946 4.5 58 Richmond City, VA........ 7.3 150.2 -3.2 100 1,021 0.9 280 Virginia Beach City, VA.. 11.5 164.4 -3.3 107 756 4.0 83 Clark, WA................ 13.3 126.8 -2.2 41 842 3.2 129 King, WA................. 82.1 1,119.1 -4.7 215 1,172 3.6 110 Kitsap, WA............... 6.8 81.6 -1.8 24 858 4.6 55 Pierce, WA............... 21.9 261.4 -3.4 117 846 3.9 87 Snohomish, WA............ 18.9 238.1 -5.2 245 969 4.4 61 Spokane, WA.............. 16.2 198.2 -4.1 170 771 4.8 43 Thurston, WA............. 7.4 97.3 -2.2 41 830 2.6 180 Whatcom, WA.............. 7.1 77.5 -3.6 134 734 3.7 103 Yakima, WA............... 8.9 90.9 -2.5 56 640 2.4 197 Kanawha, WV.............. 6.0 105.7 -3.3 107 819 2.4 197 Brown, WI................ 6.7 143.6 -3.6 134 851 3.8 96 Dane, WI................. 13.9 295.6 -3.1 88 897 2.4 197 Milwaukee, WI............ 21.2 470.3 -4.9 225 948 2.9 153 Outagamie, WI............ 5.0 100.3 -4.9 225 792 1.1 273 Racine, WI............... 4.1 70.5 -6.1 289 867 -1.1 313 Waukesha, WI............. 12.9 218.1 -6.4 300 919 0.1 304 Winnebago, WI............ 3.7 87.9 -2.5 56 870 1.5 252 San Juan, PR............. 11.8 276.8 -4.6 (8) 653 4.8 (8) (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 334 U.S. counties comprise 71.4 percent of the total covered workers in the U.S. (2) Data are preliminary. (3) Includes areas not officially designated as counties. See Technical Note. (4) Average weekly wages were calculated using unrounded data. (5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands. (7) Data do not meet BLS or State agency disclosure standards. (8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties, fourth quarter 2009(2) Employment Average weekly wage(3) Establishments, fourth quarter County by NAICS supersector 2009 Percent Percent (thousands) December change, Average change, 2009 December weekly fourth (thousands) 2008-09(4) wage quarter 2008-09(4) United States(5)............................. 9,085.0 128,334.9 -4.1 $942 2.5 Private industry........................... 8,790.5 106,313.0 -4.9 942 2.4 Natural resources and mining............. 126.9 1,649.6 -8.5 985 -1.1 Construction............................. 827.3 5,558.7 -16.2 1,053 0.1 Manufacturing............................ 349.9 11,484.8 -10.9 1,148 4.9 Trade, transportation, and utilities..... 1,886.7 25,057.0 -4.8 783 2.2 Information.............................. 145.7 2,766.2 -6.3 1,448 6.4 Financial activities..................... 834.7 7,498.6 -4.6 1,422 2.3 Professional and business services....... 1,534.3 16,512.5 -4.9 1,237 2.9 Education and health services............ 876.0 18,597.7 1.6 911 4.5 Leisure and hospitality.................. 742.6 12,621.7 -2.6 399 2.3 Other services........................... 1,261.9 4,343.0 -2.4 589 1.4 Government................................. 294.5 22,022.0 -0.4 942 3.1 Los Angeles, CA.............................. 434.0 3,926.0 -5.3 1,099 2.0 Private industry........................... 430.1 3,342.6 -5.7 1,093 2.4 Natural resources and mining............. 0.5 9.3 -10.6 1,473 16.6 Construction............................. 13.6 107.1 -21.2 1,154 1.3 Manufacturing............................ 13.9 375.8 -10.5 1,169 6.3 Trade, transportation, and utilities..... 52.4 752.7 -6.1 858 3.5 Information.............................. 8.8 199.0 -4.4 2,045 7.2 Financial activities..................... 23.2 217.3 -6.1 1,487 1.5 Professional and business services....... 42.5 526.0 -8.1 1,339 1.7 Education and health services............ 28.5 504.6 0.6 1,034 5.6 Leisure and hospitality.................. 27.4 380.2 -4.5 908 -3.4 Other services........................... 204.6 253.7 -1.4 449 -1.3 Government................................. 3.9 583.4 -2.4 1,136 -0.4 Cook, IL..................................... 142.6 2,369.9 -4.5 1,142 2.1 Private industry........................... 141.2 2,062.3 -5.0 1,141 1.2 Natural resources and mining............. 0.1 0.9 -11.2 1,071 -0.6 Construction............................. 12.2 69.1 -16.0 1,407 -4.6 Manufacturing............................ 6.8 196.5 -10.1 1,158 3.7 Trade, transportation, and utilities..... 27.5 444.4 -5.7 843 0.8 Information.............................. 2.6 52.1 -5.9 1,622 9.1 Financial activities..................... 15.4 190.9 -6.6 2,063 2.0 Professional and business services....... 29.5 396.2 -6.7 1,542 0.7 Education and health services............ 14.5 392.6 1.6 976 5.1 Leisure and hospitality.................. 12.2 220.9 -2.4 454 2.0 Other services........................... 15.1 93.9 -2.9 792 1.4 Government................................. 1.4 307.6 -1.0 1,148 8.4 New York, NY................................. 118.1 2,294.4 -3.9 1,878 1.1 Private industry........................... 117.9 1,845.7 -4.7 2,072 1.5 Natural resources and mining............. 0.0 0.1 -8.9 1,795 12.0 Construction............................. 2.2 31.0 -15.3 2,062 6.1 Manufacturing............................ 2.7 27.3 -17.4 1,582 5.2 Trade, transportation, and utilities..... 21.0 241.2 -5.5 1,316 1.6 Information.............................. 4.4 124.9 -7.4 2,144 4.1 Financial activities..................... 18.7 345.1 -7.2 4,264 4.6 Professional and business services....... 24.6 459.7 -6.3 2,148 -1.1 Education and health services............ 8.8 298.9 1.3 1,180 4.1 Leisure and hospitality.................. 11.9 223.7 -1.2 927 3.8 Other services........................... 18.1 88.2 -2.0 1,112 1.0 Government................................. 0.3 448.7 -0.8 1,087 2.3 Harris, TX................................... 98.7 1,990.2 -4.3 1,195 0.7 Private industry........................... 98.2 1,726.5 -5.3 1,225 0.8 Natural resources and mining............. 1.5 80.3 -5.9 3,130 9.4 Construction............................. 6.6 134.7 -14.5 1,229 1.1 Manufacturing............................ 4.6 166.9 -12.3 1,494 1.4 Trade, transportation, and utilities..... 22.4 421.5 -4.7 1,027 -0.5 Information.............................. 1.4 30.2 -4.8 1,381 -0.4 Financial activities..................... 10.6 114.2 -4.0 1,456 -3.4 Professional and business services....... 19.8 311.4 -7.3 1,494 2.5 Education and health services............ 10.7 232.9 4.0 990 3.3 Leisure and hospitality.................. 7.9 175.0 -0.8 414 2.7 Other services........................... 12.4 58.7 -2.6 660 -2.4 Government................................. 0.5 263.7 2.4 997 1.0 Maricopa, AZ................................. 98.7 1,626.8 -6.5 923 3.4 Private industry........................... 98.0 1,407.7 -6.9 920 2.8 Natural resources and mining............. 0.5 7.9 -6.4 857 -16.6 Construction............................. 9.8 82.8 -28.5 998 1.1 Manufacturing............................ 3.3 106.7 -11.5 1,272 4.4 Trade, transportation, and utilities..... 22.4 345.4 -5.5 824 3.3 Information.............................. 1.5 27.5 -6.8 1,227 11.0 Financial activities..................... 12.1 134.3 -4.5 1,094 2.5 Professional and business services....... 22.3 265.2 -7.9 1,007 1.6 Education and health services............ 10.3 224.1 3.2 1,037 3.9 Leisure and hospitality.................. 7.1 166.3 -5.9 440 4.3 Other services........................... 7.1 46.6 -4.6 655 6.0 Government................................. 0.7 219.1 -4.0 940 6.6 Dallas, TX................................... 67.8 1,409.9 -4.3 1,129 0.5 Private industry........................... 67.3 1,240.9 -4.9 1,144 0.3 Natural resources and mining............. 0.6 8.3 -0.5 3,746 -22.4 Construction............................. 4.2 67.6 -15.9 1,110 3.4 Manufacturing............................ 3.0 116.5 -11.2 1,279 (6) Trade, transportation, and utilities..... 14.9 288.7 -5.1 997 0.7 Information.............................. 1.6 45.5 -5.0 1,564 3.2 Financial activities..................... 8.6 137.0 (6) 1,427 (6) Professional and business services....... 14.8 251.3 -7.4 1,377 0.0 Education and health services............ 6.9 162.2 6.1 1,067 1.0 Leisure and hospitality.................. 5.4 124.9 -3.0 514 4.5 Other services........................... 6.9 38.1 -2.2 672 -0.3 Government................................. 0.5 169.0 -0.1 1,018 3.2 Orange, CA................................... 102.8 1,361.4 -6.2 1,065 2.0 Private industry........................... 101.5 1,215.9 -6.5 1,067 2.2 Natural resources and mining............. 0.2 3.3 -16.9 637 -5.5 Construction............................. 6.7 67.8 -20.0 1,199 -2.1 Manufacturing............................ 5.1 149.4 -11.1 1,299 6.1 Trade, transportation, and utilities..... 16.6 253.8 -6.7 971 3.3 Information.............................. 1.3 26.0 -10.0 1,546 7.3 Financial activities..................... 10.2 104.8 (6) 1,643 3.4 Professional and business services....... 19.0 238.5 (6) 1,279 0.6 Education and health services............ 10.2 152.1 0.0 1,014 5.7 Leisure and hospitality.................. 7.1 166.5 -3.1 417 3.5 Other services........................... 20.0 47.8 -2.7 556 -0.7 Government................................. 1.4 145.5 -3.1 1,048 0.4 San Diego, CA................................ 99.4 1,245.3 -4.9 1,019 3.7 Private industry........................... 98.1 1,021.4 -5.8 1,005 4.4 Natural resources and mining............. 0.7 8.6 -7.6 613 4.8 Construction............................. 6.7 57.0 -19.2 1,182 3.6 Manufacturing............................ 3.1 92.0 -9.7 1,411 7.5 Trade, transportation, and utilities..... 13.9 205.9 -5.6 785 (6) Information.............................. 1.2 36.3 -6.1 2,156 9.8 Financial activities..................... 9.0 69.6 -5.1 1,185 0.5 Professional and business services....... 16.3 197.0 -6.3 1,320 4.8 Education and health services............ 8.3 144.6 2.5 990 4.3 Leisure and hospitality.................. 7.0 149.2 -6.3 442 3.3 Other services........................... 27.7 56.8 -3.6 512 7.6 Government................................. 1.3 224.0 -0.9 1,082 0.0 King, WA..................................... 82.1 1,119.1 -4.7 1,172 3.6 Private industry........................... 81.6 962.2 -5.4 1,180 3.4 Natural resources and mining............. 0.4 2.7 -7.9 1,321 -16.3 Construction............................. 6.6 48.8 -22.8 1,255 5.0 Manufacturing............................ 2.4 98.5 -9.4 1,504 3.7 Trade, transportation, and utilities..... 15.2 209.1 -5.5 996 4.0 Information.............................. 1.8 78.4 -4.3 2,016 2.1 Financial activities..................... 6.9 66.2 -7.9 1,515 6.4 Professional and business services....... 14.5 171.9 -7.5 1,449 5.3 Education and health services............ 6.9 131.6 1.8 968 8.0 Leisure and hospitality.................. 6.4 105.8 -2.7 469 4.5 Other services........................... 20.5 49.2 12.6 598 -5.7 Government................................. 0.5 157.0 0.0 1,122 4.9 Miami-Dade, FL............................... 85.0 959.7 -4.5 949 2.9 Private industry........................... 84.6 811.8 -4.7 919 1.7 Natural resources and mining............. 0.5 9.5 -3.2 483 7.3 Construction............................. 5.6 32.9 -21.1 980 0.8 Manufacturing............................ 2.6 35.5 -14.1 914 10.1 Trade, transportation, and utilities..... 23.3 242.0 -4.4 834 2.8 Information.............................. 1.5 17.4 -8.6 1,340 6.3 Financial activities..................... 9.5 62.2 -6.2 1,397 0.1 Professional and business services....... 17.7 123.4 -7.0 1,215 -1.0 Education and health services............ 9.6 150.2 3.0 915 1.7 Leisure and hospitality.................. 6.1 103.5 -1.9 538 6.5 Other services........................... 7.5 34.7 -4.9 576 -0.9 Government................................. 0.4 147.8 -3.2 1,112 9.3 (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. (2) Data are preliminary. (3) Average weekly wages were calculated using unrounded data. (4) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (5) Totals for the United States do not include data for Puerto Rico or the Virgin Islands. (6) Data do not meet BLS or State agency disclosure standards.
Table 3. Covered(1) establishments, employment, and wages in the largest county by state, fourth quarter 2009(2) Employment Average weekly wage(4) Establishments, fourth quarter County(3) 2009 Percent Percent (thousands) December change, Average change, 2009 December weekly fourth (thousands) 2008-09(5) wage quarter 2008-09(5) United States(6)......... 9,085.0 128,334.9 -4.1 $942 2.5 Jefferson, AL............ 18.1 336.1 -5.6 946 2.5 Anchorage Borough, AK.... 8.2 147.6 -0.3 1,005 3.5 Maricopa, AZ............. 98.7 1,626.8 -6.5 923 3.4 Pulaski, AR.............. 15.1 244.2 -2.7 863 1.6 Los Angeles, CA.......... 434.0 3,926.0 -5.3 1,099 2.0 Denver, CO............... 25.0 420.2 -4.7 1,154 3.4 Hartford, CT............. 25.4 486.0 -3.8 1,153 3.6 New Castle, DE........... 17.8 264.6 -5.9 1,070 1.9 Washington, DC........... 34.8 686.7 -0.1 1,614 2.7 Miami-Dade, FL........... 85.0 959.7 -4.5 949 2.9 Fulton, GA............... 39.3 697.4 -5.0 1,207 1.9 Honolulu, HI............. 25.0 435.3 -3.2 875 2.9 Ada, ID.................. 14.5 193.7 -4.9 824 1.5 Cook, IL................. 142.6 2,369.9 -4.5 1,142 2.1 Marion, IN............... 24.0 547.0 -3.8 942 3.1 Polk, IA................. 14.8 265.7 -3.1 933 3.1 Johnson, KS.............. 20.9 298.8 -5.0 982 3.4 Jefferson, KY............ 22.0 409.9 -3.2 908 4.2 East Baton Rouge, LA..... 14.7 259.1 -3.1 897 2.6 Cumberland, ME........... 12.3 168.0 -3.2 863 4.7 Montgomery, MD........... 32.5 447.4 -2.1 1,294 6.2 Middlesex, MA............ 47.9 803.0 -2.8 1,344 3.5 Wayne, MI................ 31.1 662.6 -7.1 1,036 0.5 Hennepin, MN............. 40.7 802.6 -4.3 1,152 0.7 Hinds, MS................ 6.3 125.0 -2.4 832 3.4 St. Louis, MO............ 32.1 571.0 -4.7 1,006 1.5 Yellowstone, MT.......... 5.9 75.7 -3.4 768 3.9 Douglas, NE.............. 15.9 312.1 -3.1 874 3.9 Clark, NV................ 49.4 809.7 -7.0 872 1.9 Hillsborough, NH......... 12.1 188.3 -3.9 1,065 0.2 Bergen, NJ............... 34.5 432.8 -3.8 1,205 1.7 Bernalillo, NM........... 17.5 317.3 -3.7 850 4.4 New York, NY............. 118.1 2,294.4 -3.9 1,878 1.1 Mecklenburg, NC.......... 32.3 534.2 -5.7 1,042 2.5 Cass, ND................. 5.9 99.3 -1.4 795 2.1 Cuyahoga, OH............. 36.7 689.8 -4.7 939 1.2 Oklahoma, OK............. 24.1 408.0 -4.4 870 1.9 Multnomah, OR............ 28.1 421.9 -4.9 953 1.9 Allegheny, PA............ 35.1 668.8 -2.4 1,003 2.9 Providence, RI........... 17.7 267.0 -4.0 951 1.9 Greenville, SC........... 12.4 224.0 -4.5 820 2.9 Minnehaha, SD............ 6.5 113.2 -2.5 777 5.0 Shelby, TN............... 19.4 471.5 -5.0 971 3.9 Harris, TX............... 98.7 1,990.2 -4.3 1,195 0.7 Salt Lake, UT............ 37.5 562.1 -4.1 888 4.7 Chittenden, VT........... 6.0 93.2 -2.3 937 4.6 Fairfax, VA.............. 34.3 574.6 -1.9 1,489 5.2 King, WA................. 82.1 1,119.1 -4.7 1,172 3.6 Kanawha, WV.............. 6.0 105.7 -3.3 819 2.4 Milwaukee, WI............ 21.2 470.3 -4.9 948 2.9 Laramie, WY.............. 3.2 42.6 -3.2 778 3.5 San Juan, PR............. 11.8 276.8 -4.6 653 4.8 St. Thomas, VI........... 1.8 23.3 -2.7 696 3.7 (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. (2) Data are preliminary. (3) Includes areas not officially designated as counties. See Technical Note. (4) Average weekly wages were calculated using unrounded data. (5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
Table 4. Covered(1) establishments, employment, and wages by state, fourth quarter 2009(2) Employment Average weekly wage(3) Establishments, fourth quarter State 2009 Percent Percent (thousands) December change, Average change, 2009 December weekly fourth (thousands) 2008-09 wage quarter 2008-09 United States(4)......... 9,085.0 128,334.9 -4.1 $942 2.5 Alabama.................. 117.5 1,819.9 -4.7 818 3.4 Alaska................... 21.4 302.4 -0.5 959 3.5 Arizona.................. 154.1 2,406.2 -6.0 876 3.3 Arkansas................. 86.1 1,136.2 -2.8 725 2.5 California............... 1,374.0 14,476.4 -5.3 1,074 3.1 Colorado................. 171.7 2,183.6 -4.9 965 3.5 Connecticut.............. 112.0 1,620.1 -4.0 1,192 2.3 Delaware................. 28.6 398.3 -5.0 960 2.1 District of Columbia..... 34.8 686.7 -0.1 1,614 2.7 Florida.................. 599.3 7,208.9 -5.0 855 3.6 Georgia.................. 271.6 3,773.5 -4.9 875 2.6 Hawaii................... 39.3 592.5 -3.7 843 2.7 Idaho.................... 55.8 604.3 -4.7 708 2.2 Illinois................. 376.4 5,529.4 -4.6 1,008 2.3 Indiana.................. 159.9 2,709.7 -4.3 781 2.2 Iowa..................... 94.6 1,436.2 -3.3 771 2.1 Kansas................... 88.1 1,309.8 -4.4 792 2.9 Kentucky................. 108.2 1,726.2 -3.1 781 3.4 Louisiana................ 127.0 1,842.8 -3.5 833 0.4 Maine.................... 50.2 579.0 -2.8 759 3.3 Maryland................. 162.4 2,462.9 -2.8 1,054 4.5 Massachusetts............ 215.5 3,142.5 -3.0 1,176 1.8 Michigan................. 252.2 3,767.7 -5.6 913 1.1 Minnesota................ 166.0 2,559.4 -3.8 928 2.3 Mississippi.............. 70.7 1,076.5 -3.7 697 2.7 Missouri................. 174.3 2,598.7 -3.8 816 -3.2 Montana.................. 42.5 419.4 -3.3 695 2.5 Nebraska................. 60.5 896.6 -2.9 756 3.6 Nevada................... 74.9 1,123.2 -6.9 875 1.4 New Hampshire............ 48.9 605.8 -3.2 958 2.4 New Jersey............... 270.8 3,806.6 -2.9 1,143 1.6 New Mexico............... 54.1 787.0 -4.2 794 3.3 New York................. 586.4 8,445.4 -2.6 1,190 1.7 North Carolina........... 251.3 3,802.2 -5.0 818 3.2 North Dakota............. 26.0 353.6 -0.2 752 3.7 Ohio..................... 288.1 4,911.8 -4.9 840 2.9 Oklahoma................. 101.9 1,486.4 -4.8 763 0.9 Oregon................... 130.6 1,593.3 -4.8 829 2.5 Pennsylvania............. 342.0 5,474.5 -3.1 931 3.8 Rhode Island............. 35.3 448.1 -3.5 912 2.9 South Carolina........... 112.7 1,748.6 -4.9 763 4.4 South Dakota............. 31.0 386.0 -2.4 688 3.8 Tennessee................ 140.5 2,572.3 -4.5 849 2.9 Texas.................... 567.1 10,146.9 -3.5 944 1.2 Utah..................... 85.7 1,158.1 -4.5 796 3.2 Vermont.................. 24.6 296.4 -2.7 804 3.7 Virginia................. 231.7 3,551.6 -2.8 994 4.3 Washington............... 235.0 2,776.6 -3.7 952 3.6 West Virginia............ 48.5 693.6 -2.9 752 2.5 Wisconsin................ 158.2 2,634.2 -4.4 810 2.1 Wyoming.................. 25.1 266.9 -6.3 831 -2.2 Puerto Rico.............. 50.0 977.6 -5.2 552 4.5 Virgin Islands........... 3.5 43.9 -3.7 746 2.2 (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. (2) Data are preliminary. (3) Average weekly wages were calculated using unrounded data. (4) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.